PROCEEDINGS VOLUME 10664
SPIE COMMERCIAL + SCIENTIFIC SENSING AND IMAGING | 15-19 APRIL 2018
Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping III
Proceedings Volume 10664 is from: Logo
SPIE COMMERCIAL + SCIENTIFIC SENSING AND IMAGING
15-19 April 2018
Orlando, Florida, United States
Collecting Reliable Image Data with UAVs
Proc. SPIE 10664, Implications of sensor inconsistencies and remote sensing error in the use of small unmanned aerial systems for generation of information products for agricultural management, 1066402 (21 May 2018); https://doi.org/10.1117/12.2305826
Proc. SPIE 10664, Ground-truthing of UAV-based remote sensing data of citrus plants, 1066403 (21 May 2018); https://doi.org/10.1117/12.2303614
Proc. SPIE 10664, Quality assessment of radiometric calibration of UAV image mosaics, 1066404 (16 July 2018); https://doi.org/10.1117/12.2305635
Proc. SPIE 10664, Correction of in-flight luminosity variations in multispectral UAS images, using a luminosity sensor and camera pair for improved biomass estimation in precision agriculture, 1066405 (21 May 2018); https://doi.org/10.1117/12.2303804
Proc. SPIE 10664, An initial exploration of vicarious and in-scene calibration techniques for small unmanned aircraft systems, 1066406 (21 May 2018); https://doi.org/10.1117/12.2302744
Proc. SPIE 10664, Behavior of vegetation/soil indices in shaded and sunlit pixels and evaluation of different shadow compensation methods using UAV high-resolution imagery over vineyards, 1066407 (21 May 2018); https://doi.org/10.1117/12.2305883
Proc. SPIE 10664, Studying CO2 from plant respiration in controlled and natural environment: How can plant breeding industry benefit from it? (Conference Presentation), 1066408 (); https://doi.org/10.1117/12.2315601
Proximal and Remote Sensing for Phenotyping
Proc. SPIE 10664, Detection of canola flowering using proximal and aerial remote sensing techniques, 1066409 (21 May 2018); https://doi.org/10.1117/12.2304054
Proc. SPIE 10664, Vinobot and vinoculer: from real to simulated platforms, 106640A (21 May 2018); https://doi.org/10.1117/12.2316341
Proc. SPIE 10664, Phenotyping of sorghum panicles using unmanned aerial system (UAS) data, 106640B (16 July 2018); https://doi.org/10.1117/12.2305099
Proc. SPIE 10664, Calibrated plant height estimates with structure from motion from fixed-wing UAV images, 106640D (21 May 2018); https://doi.org/10.1117/12.2305746
Thermal and Hyperspectral Imaging from UAVs
Proc. SPIE 10664, Inter-comparison of thermal measurements using ground-based sensors, UAV thermal cameras, and eddy covariance radiometers, 106640E (16 July 2018); https://doi.org/10.1117/12.2305832
Proc. SPIE 10664, A detailed study on accuracy of uncooled thermal cameras by exploring the data collection workflow, 106640F (21 May 2018); https://doi.org/10.1117/12.2305217
Proc. SPIE 10664, Image quality and accuracy of different thermal sensor at varying operation parameters (Conference Presentation), 106640G (); https://doi.org/10.1117/12.2307168
Proc. SPIE 10664, A low-cost method for collecting hyperspectral measurements from a small unmanned aircraft system, 106640H (21 May 2018); https://doi.org/10.1117/12.2305934
Proc. SPIE 10664, Hyperspectral detection of methane stressed vegetation, 106640I (21 May 2018); https://doi.org/10.1117/12.2304045
Detecting Yield, Disease, and Water Stress from UAVs
Proc. SPIE 10664, Multispectral remote sensing for yield estimation using high-resolution imagery from an unmanned aerial vehicle, 106640K (21 May 2018); https://doi.org/10.1117/12.2305888
Proc. SPIE 10664, Disease detection and mitigation in a cotton crop with UAV remote sensing, 106640L (15 May 2018); https://doi.org/10.1117/12.2307018
Proc. SPIE 10664, An unmanned aerial system for the detection of crops with undergraduate project-based learning, 106640M (21 May 2018); https://doi.org/10.1117/12.2319050
Proc. SPIE 10664, Experimental approach to detect water stress in ornamental plants using sUAS-imagery, 106640N (21 May 2018); https://doi.org/10.1117/12.2304739
Analytics for UAV-based Crop Management
Proc. SPIE 10664, Machine learning techniques for the assessment of citrus plant health using UAV-based digital images, 106640O (21 May 2018); https://doi.org/10.1117/12.2303989
Proc. SPIE 10664, Unmanned aerial system based cotton genotype selection using machine learning (Conference Presentation), 106640P (); https://doi.org/10.1117/12.2323858
Proc. SPIE 10664, Evaluation of multispectral unmanned aerial systems for irrigation management, 106640Q (16 July 2018); https://doi.org/10.1117/12.2305076
Innovative UAV Applications
Proc. SPIE 10664, UAV videos to extend research to producers, 106640R (16 July 2018); https://doi.org/10.1117/12.2305013
Proc. SPIE 10664, A comparison of manned and unmanned aerial Lidar systems in the context of sustainable forest management, 106640S (21 May 2018); https://doi.org/10.1117/12.2304850
Proc. SPIE 10664, Spatial analysis of multispectral and thermal imagery from multiple platforms, 106640T (21 May 2018); https://doi.org/10.1117/12.2305896
Proc. SPIE 10664, Evaluating the capabilities of Sentinel-2 and Tetracam RGB+3 for multi-temporal detection of thrips on capsicum, 106640U (21 May 2018); https://doi.org/10.1117/12.2305358
Poster Session
Proc. SPIE 10664, Using hyperspectral sensors for crop vegetation status monitoring in precision agriculture, 106640W (21 May 2018); https://doi.org/10.1117/12.2305156
Proc. SPIE 10664, MoniSCAN: software for multispectral monitoring of the crops vegetation status, 106640X (21 May 2018); https://doi.org/10.1117/12.2305197
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